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» Kernel Based Detection of Mislabeled Training Examples
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CVPR
2005
IEEE
14 years 9 months ago
Online Detection and Classification of Moving Objects Using Progressively Improving Detectors
Boosting based detection methods have successfully been used for robust detection of faces and pedestrians. However, a very large amount of labeled examples are required for train...
Omar Javed, Saad Ali, Mubarak Shah
EMNLP
2007
13 years 8 months ago
A Discriminative Learning Model for Coordinate Conjunctions
We propose a sequence-alignment based method for detecting and disambiguating coordinate conjunctions. In this method, averaged perceptron learning is used to adapt the substituti...
Masashi Shimbo, Kazuo Hara
RSFDGRC
2005
Springer
156views Data Mining» more  RSFDGRC 2005»
14 years 27 days ago
Intrusion Detection System Based on Multi-class SVM
In this paper, we propose a new intrusion detection model, which keeps advantages of existing misuse detection model and anomaly detection model and resolves their problems. This ...
Hansung Lee, Jiyoung Song, Daihee Park
CVPR
2004
IEEE
14 years 9 months ago
An Unsupervised, Online Learning Framework for Moving Object Detection
Object detection with a learned classifier has been applied successfully to difficult tasks such as detecting faces and pedestrians. Systems using this approach usually learn the ...
Vinod Nair, James J. Clark
ICDM
2008
IEEE
176views Data Mining» more  ICDM 2008»
14 years 1 months ago
Inlier-Based Outlier Detection via Direct Density Ratio Estimation
We propose a new statistical approach to the problem of inlier-based outlier detection, i.e., finding outliers in the test set based on the training set consisting only of inlier...
Shohei Hido, Yuta Tsuboi, Hisashi Kashima, Masashi...